Risk stratification and molecular targeting have been key to increasing cure rates for pediatric cancers in high-income countries. In contrast, precise diagnosis in low-resource settings is hindered by insufficient pathology infrastructure. The Global HOPE program aims to improve outcomes for pediatric cancer in Sub-Saharan Africa (SSA) by building local clinical care and diagnostic capacity. This study aimed to assess the feasibility of implementing molecular assays to improve leukemia diagnoses in SSA. Custom NanoString nCounter gene fusion assays, previously validated in the US, were used to test samples from suspected leukemia patients. The NanoString platform was chosen due to relatively low cost, minimal technical and bioinformatics expertise required, ability to test sub-optimal RNA, and rapid turnaround time. Fusion results were analyzed blindly, then compared to morphology and flow cytometry results. Of 117 leukemia samples, 74 were fusion-positive, 30 were negative, 7 were not interpretable, and 6 failed RNA quality. Nine additional samples were negative for leukemia by flow cytometry and negative for gene fusions. All 74 gene fusions aligned with the immunophenotype determined by flow cytometry. Fourteen samples had additional information available to further confirm the accuracy of the gene fusion results. The testing provided a more precise diagnosis in >60% of cases, and 9 cases were identified that could be treated with an available tyrosine kinase inhibitor, if detected at diagnosis. As risk-stratified and targeted therapies become more available in SSA, implementing this testing in real-time will enable the treatment of pediatric cancer to move toward incorporating risk stratification for optimized therapy.

UNASSIGNED: Clinical trials for reducing fibrosis in steatotic liver disease (SLD) have targeted macrophages with variable results. We evaluated intrahepatic macrophages in patients with SLD to determine if activity scores or fibrosis stages influenced phenotypes and expression of druggable targets, such as CCR2 and galectin-3.
UNASSIGNED: Liver biopsies from controls or patients with minimal or advanced fibrosis were subject to gene expression analysis using nCounter to determine differences in macrophage-related genes (n = 30). To investigate variability among individual patients, we compared additional biopsies by staining them with multiplex antibody panels (CD68/CD14/CD16/CD163/Mac387 or CD163/CCR2/galectin-3/Mac387) followed by spectral imaging and spatial analysis. Algorithms that utilize deep learning/artificial intelligence were applied to create cell cluster plots, phenotype profile maps, and to determine levels of protein expression (n = 34).
UNASSIGNED: Several genes known to be pro-fibrotic (e.g. CD206, TREM2, CD163, and ARG1) showed either no significant differences or significantly decreased with advanced fibrosis. Although marked variability in gene expression was observed in individual patients with cirrhosis, several druggable targets and their ligands (e.g. CCR2, CCR5, CCL2, CCL5, and LGALS3) were significantly increased when compared to patients with minimal fibrosis. Antibody panels identified populations that were significantly increased (e.g. Mac387+), decreased (e.g. CD14+), or enriched (e.g. interactions of Mac387) in patients that had progression of disease or advanced fibrosis. Despite heterogeneity in patients with SLD, several macrophage phenotypes and druggable targets showed a positive correlation with increasing NAFLD activity scores and fibrosis stages.
UNASSIGNED: Patients with SLD have markedly varied macrophage- and druggable target-related gene and protein expression in their livers. Several patients had relatively high expression, while others were like controls. Overall, patients with more advanced disease had significantly higher expression of CCR2 and galectin-3 at both the gene and protein levels.
UNASSIGNED: Appreciating individual differences within the hepatic microenvironment of patients with SLD may be paramount to developing effective treatments. These results may explain why such a small percentage of patients have responded to macrophage-targeting therapies and provide additional support for precision medicine-guided treatment of chronic liver diseases.

Triple-negative breast cancer (TNBC) is a rare and aggressive breast cancer subtype. Unlike the estrogen receptor-positive subtype, whose recurrence risk can be predicted by gene expression-based signature, TNBC is more heterogeneous, with diverse drug sensitivity levels to standard regimens. This study explored the benefit of gene expression-based profiling for classifying the molecular subtypes of Thai TNBC patients.
The nCounter-based Breast 360 gene expression was used to classify Thai TNBC retrospective cohort subgroups. Their expression profiles were then compared against the previously established TNBC classification system. The differential characteristics of the tumor microenvironment and DNA damage repair signatures across subgroups were also explored.
Thai TNBC cohort could be classified into four main subgroups, corresponding to the LAR, BL-2, and M subtypes based on Lehmann\'s TNBC classification. The PAM50 gene set classified most samples as basal-like subtypes except for Group 1. Group 1 exhibited similar enrichment of the metabolic and hormone response pathways to the LAR subtype. Group 2 shared pathway activation with the BL-2 subtype. Group 3 showed an increase in the EMT pathway, similar to the M subtype. Group 4 showed no correlation with Lehmann\'s TNBC. The tumor microenvironment (TME) analysis showed high TME cell abundance with increased expression of immune blockade genes in Group 2. Group 4 exhibited low TME cell abundance and reduced immune blockade gene expressions. We also observed distinct signatures of the DNA double-strand break repair genes in Group 1.
Our study reported unique characteristics between the four TNBC subgroups and showed the potential use of immune checkpoint and PARP inhibitors in subsets of Thai TNBC patients. Our findings warrant further clinical investigation to validate TNBC\'s sensitivity to these regimens.

DNA sequencing assays have been used to characterize the vaginal microbiome and to identify associations with clinical outcomes. The purpose of this study was to evaluate the utility of the NanoString nCounter platform, a more efficient assay compared to sequencing, for the characterization of vaginal microbial communities. A panel of NanoString nCounter probes was designed to detect common vaginal bacteria and viruses with relevance to reproductive health. A defined synthetic community of microbes and 43 clinical samples were interrogated with NanoString nCounter assays and compared to known compositions or metagenomic shotgun sequencing (MSS) results. The NanoString nCounter platform and MSS were able to distinguish closely related microbes. In clinical samples, the relative abundance of bacterial species was similar between the two assays. The assays sometimes disagreed when targets were present at low abundance. More viruses were detected by MSS than by nCounter. However, the nCounter assays are able to provide results in about 30 h with minimal hands-on time, whereas MSS requires at least 138 to 178 h with extensive hands-on time. The reagent cost for the two assays was similar, but the overall cost of the nCounter was lower due to the minimal hands-on time. MSS can be used to inform the design of a targeted multiplex panel for the assessment of vaginal microbial communities, thereby allowing for more cost-effective and rapid screening of patient samples for research studies. The sensitivity for low abundance microbes could be improved, possibly by adding additional target amplification cycles before nCounter assessment. This approach has potential as an assay with both research and clinical applications. IMPORTANCE Metagenomic shotgun sequencing can inform the design of a targeted multiplex panel by which the NanoString nCounter platform can assess vaginal microbial communities, thereby allowing for more cost-effective and rapid screening of patient samples.

Treatment failures of glioblastoma (GBM) occur within high-dose radiation fields. We hypothesized that this is due to increased capacity for DNA damage repair in GBM. We identified 24 adult GBM patients treated with maximal safe resection followed by radiation with concurrent and adjuvant temozolomide. The mRNA from patients was quantified using NanoString Technologies\' nCounter platform and compared with 12 non-neoplastic temporal lobe tissue samples as a control. Differential expression analysis identified seven DNA repair genes significantly upregulated in GBM tissues relative to controls (>4-fold difference, adjusted p values < 0.001). Among these seven genes, Cox proportional hazards models identified RAD51 to be associated with an increased risk of death (HR = 3.49; p = 0.03). Kaplan-Meier (KM) analysis showed that patients with high RAD51 expression had significantly shorter OS compared to low levels (median OS of 10.6 mo. vs 20.1 mo.; log-rank p = 0.03). Our findings were validated in a larger external dataset of 162 patients using publicly available gene expression data quantified by the same NanoString technology (median OS of 13.8 mo. vs. 17.4 mo; log-rank p = 0.006). Within this uniformly treated GBM population, RAD51, in the homologous recombination pathway, was overexpressed (vs. normal brain) and inversely correlated with OS. High RAD51 expression may be a prognostic biomarker and a therapeutic target in GBM.

Breast cancer intrinsic subtypes have been identified based on the transcription of a predefined gene expression (GE) profiles and algorithm (prediction analysis of microarray 50 gene set, PAM50). The present study compared molecular subtyping with oligonucleotide microarray and NanoString nCounter assay. A total of 109 Taiwanese breast cancers (24 with adjacent normal breast tissues) were assayed with Affymetrix Human Genome U133 plus 2.0 microarrays and 144 were assayed with the NanoString nCounter while 64 patients were assayed for both platforms. Subtyping with the nearest centroid (single sample prediction (SSP)) was performed, and 16 out of 24 (67%) matched normal breasts were categorized as the normal breast-like subtype. For 64 breast cancers assayed for both platforms, 41 (65%, one unclassified by microarray) were predicted with an identical subtype, resulting in a fair κ statistic of 0.60. Taking nCounter subtyping as the gold standard, prediction accuracy was 43% (3/7), 81% (13/16), 25% (5/20), and 100% (20/20) for basal-like, human epidermal growth factor receptor II (HER2)-enriched, luminal A and luminal B subtypes predicted from microarray GE profiles. Microarray identified more luminal B cases from luminal A subtype predicted by nCounter. It is not uncommon to use microarray for breast cancer molecular subtyping for research. Our study showed that fundamental discrepancy existed between distinct GE assays, and cross-platform equivalence should be carefully appraised when molecular subtyping was conducted with oligonucleotide microarray.

Segmented filamentous bacteria (SFB) and Bacteroides fragilis are known to interact with the host immune response through the aryl hydrocarbon receptor (Ahr). 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), an environmental toxicant and a high-affinity Ahr ligand has the potential to modify the effect of SFB and B. fragilis. MicroRNAs (miRNA) with their role in regulating gene expression post-transcriptionally, may potentially be used to observe such interactions between SFB, B. fragilis, and TCDD. However, little is known regarding the impact of gut microbial members on miRNA expression or its modulation in the presence of an environmental toxicant. This information is important in understanding toxicant-mediated dysbiosis in gut microbiome and the resulting human health impacts. In this study, C57BL/6 germ-free (GF) mice were colonized with SFB and B. fragilis and administered 30 μg/kg TCDD every 4 d for 28 d and miRNA were measured. Compared to GF mice, colonization with SFB resulted in an increase in up- and down-regulated Ileal miRNAs. TCDD treatment of this group decreased the number of upregulated miRNA and increased the number of down-regulated miRNAs. Association with SFB and B. fragilis together had a similar but less pronounced effect in response to TCDD treatment. TCDD treatment of GF mice had no miRNA expression response. Immune and inflammatory responses and T-cell differentiation were the key functions impacted by these miRNAs. Overall, these results reveal that the host response to toxicants may also depend on the presence of specific gut microbial populations.

Circular RNAs (circRNAs) have recently gained substantial attention as potential biomarkers in several human diseases, most prominently in cancer. However, the detection and quantification of circRNA biomarkers pose specific challenges owing to their circular nature. In particular, the use of enzymes, such as reverse transcriptases, may lead to impaired quantification, poor interlaboratory reproducibility and even false-positive results. Therefore, the development of methods for accurate quantification of circRNA biomarkers is a high priority. An enzyme-free and digital quantification method, named NanoString nCounter, was recently adapted for circRNA detection. In this review, I describe the advantages of using this technology for circRNA quantification as well as methodological considerations, potential pitfalls and disadvantages.

Pediatric ependymomas frequently develop in the cerebellum and are currently treated using non-specific therapies, in part, because few somatically mutated driver genes are present, and the underlying pathobiology is poorly described. Circular RNAs (circRNAs) constitute as a large class of primarily non-coding RNAs with important roles in tumorigenesis, but they have not been described in pediatric ependymomas. To advance our molecular understanding of ependymomas, we performed Next Generation Sequencing of rRNA-depleted total RNA of 10 primary ependymoma and three control samples. CircRNA expression patterns were correlated to disease stage, outcome, age, and gender. We found a profound global downregulation of circRNAs in ependymoma relative to control samples. Many differentially expressed circRNAs were discovered and circSMARCA5 and circ-FBXW7, which are described as tumor suppressors in glioma and glioblastomas in adults, were among the most downregulated. Moreover, patients with a dismal outcome clustered separately from patients with a good prognosis in unsupervised hierarchical cluster analyses. Next, NanoString nCounter experiments were performed, using a custom-designed panel targeting 66 selected circRNAs, on a larger cohort that also included medulloblastomas and pilocytic astrocytomas. These experiments indicated that circRNA expression profiles are different among distinct pediatric brain tumor subtypes. In particular, circRNAs derived from RMST, LRBA, WDR78, DRC1 and BBS9 genes were specifically upregulated in ependymomas. In conclusion, circRNAs have different expression profiles in ependymomas relative to controls and between survivors and patients with a dismal outcome, suggesting that circRNAs could be exerted as diagnostic and prognostic biomarkers in the future if further validated in larger cohorts.

Xenobiotica-metabolizing enzyme (XME) induction is a relevant biological/biochemical process vital to understanding the toxicological profile of xenobiotics. Early recognition of XME induction potential of compounds under development is therefore important, yet its determination by traditional XME activity measurements is time consuming and cost intensive. A proof-of-principle study was therefore designed due to the advent of faster and less cost-intensive methods for determination of enzyme protein and transcript levels to determine whether two such methods may substitute for traditional measurement of XME activity determinations. The results of the study show that determination of enzyme protein levels by peptide group-specific immunoaffinity enrichment/MS and/or determination of gene expression by NanoString nCounter may serve as substitutes for traditional evaluation methodology and/or as an early predictor of potential changes in liver enzymes. In this study, changes of XME activity by the known standard XME inducers phenobarbital, beta-naphthoflavone and Aroclor 1254 were demonstrated by these two methods. To investigate the applicability of these methods to demonstrate XME-inducing activity of an unknown, TS was also examined and found to be an XME inducer. More specifically, TS was found to be a phenobarbital-type inducer (likely mediated by CAR rather than PXR as nuclear receptor), but not due to Ah receptor-mediated or antioxidant response element-mediated beta-naphthoflavone-type induction. The results for TS were confirmed via enzymatic activity measurements. The results of the present study demonstrate the potential applicability of NanoString nCounter mRNA quantitation and peptide group-specific immunoaffinity enrichment/MS protein quantitation for predicting compounds under development to be inducers of liver XME activity.